In [ ]:
import matplotlib.pyplot as plt
import seaborn as sns
plt.figure(figsize=(15,7))
sns.countplot(data=df, y='Genres', order=df['Genres'].value_counts().index)
plt.title('Distribution of Game Genres')
plt.xlabel('Number of Games')
plt.show()
import pandas as pd
df = pd.read_csv('/Users/qbs/downloads/games.csv')
print(df.head())
AppID Name Release date Estimated owners Peak CCU \
0 20200 Galactic Bowling Oct 21, 2008 0 - 20000 0
1 655370 Train Bandit Oct 12, 2017 0 - 20000 0
2 1732930 Jolt Project Nov 17, 2021 0 - 20000 0
3 1355720 Henosis™ Jul 23, 2020 0 - 20000 0
4 1139950 Two Weeks in Painland Feb 3, 2020 0 - 20000 0
Required age Price DLC count \
0 0 19.99 0
1 0 0.99 0
2 0 4.99 0
3 0 5.99 0
4 0 0.00 0
About the game \
0 Galactic Bowling is an exaggerated and stylize...
1 THE LAW!! Looks to be a showdown atop a train....
2 Jolt Project: The army now has a new robotics ...
3 HENOSIS™ is a mysterious 2D Platform Puzzler w...
4 ABOUT THE GAME Play as a hacker who has arrang...
Supported languages ... \
0 ['English'] ...
1 ['English', 'French', 'Italian', 'German', 'Sp... ...
2 ['English', 'Portuguese - Brazil'] ...
3 ['English', 'French', 'Italian', 'German', 'Sp... ...
4 ['English', 'Spanish - Spain'] ...
Average playtime two weeks Median playtime forever \
0 0 0
1 0 0
2 0 0
3 0 0
4 0 0
Median playtime two weeks Developers Publishers \
0 0 Perpetual FX Creative Perpetual FX Creative
1 0 Rusty Moyher Wild Rooster
2 0 Campião Games Campião Games
3 0 Odd Critter Games Odd Critter Games
4 0 Unusual Games Unusual Games
Categories \
0 Single-player,Multi-player,Steam Achievements,...
1 Single-player,Steam Achievements,Full controll...
2 Single-player
3 Single-player,Full controller support
4 Single-player,Steam Achievements
Genres \
0 Casual,Indie,Sports
1 Action,Indie
2 Action,Adventure,Indie,Strategy
3 Adventure,Casual,Indie
4 Adventure,Indie
Tags \
0 Indie,Casual,Sports,Bowling
1 Indie,Action,Pixel Graphics,2D,Retro,Arcade,Sc...
2 NaN
3 2D Platformer,Atmospheric,Surreal,Mystery,Puzz...
4 Indie,Adventure,Nudity,Violent,Sexual Content,...
Screenshots \
0 https://cdn.akamai.steamstatic.com/steam/apps/...
1 https://cdn.akamai.steamstatic.com/steam/apps/...
2 https://cdn.akamai.steamstatic.com/steam/apps/...
3 https://cdn.akamai.steamstatic.com/steam/apps/...
4 https://cdn.akamai.steamstatic.com/steam/apps/...
Movies
0 http://cdn.akamai.steamstatic.com/steam/apps/2...
1 http://cdn.akamai.steamstatic.com/steam/apps/2...
2 http://cdn.akamai.steamstatic.com/steam/apps/2...
3 http://cdn.akamai.steamstatic.com/steam/apps/2...
4 http://cdn.akamai.steamstatic.com/steam/apps/2...
[5 rows x 39 columns]
print(df.describe())
AppID Peak CCU Required age Price DLC count \
count 7.171500e+04 71715.000000 71715.000000 71715.000000 71715.000000
mean 1.199233e+06 140.763160 0.343499 7.223156 0.615394
std 5.982204e+05 5797.045907 2.362144 11.072095 14.932957
min 1.000000e+01 0.000000 0.000000 0.000000 0.000000
25% 7.005500e+05 0.000000 0.000000 0.990000 0.000000
50% 1.176780e+06 0.000000 0.000000 4.990000 0.000000
75% 1.692260e+06 1.000000 0.000000 9.990000 0.000000
max 2.379920e+06 872138.000000 21.000000 999.000000 2366.000000
Positive Negative Achievements Recommendations \
count 7.171500e+04 71715.000000 71715.000000 7.171500e+04
mean 1.114768e+03 182.118065 21.642278 8.981311e+02
std 2.652264e+04 4975.240406 185.584866 1.947641e+04
min 0.000000e+00 0.000000 0.000000 0.000000e+00
25% 1.000000e+00 0.000000 0.000000 0.000000e+00
50% 9.000000e+00 3.000000 1.000000 0.000000e+00
75% 5.900000e+01 18.000000 19.000000 0.000000e+00
max 5.764420e+06 895978.000000 9821.000000 3.441592e+06
Average playtime forever Average playtime two weeks \
count 71715.000000 71715.000000
mean 119.160371 11.734853
std 1230.111420 203.819765
min 0.000000 0.000000
25% 0.000000 0.000000
50% 0.000000 0.000000
75% 0.000000 0.000000
max 145727.000000 19159.000000
Median playtime forever Median playtime two weeks User_Score \
count 71715.000000 71715.000000 57665.000000
mean 106.875228 12.581008 0.745519
std 1641.347714 221.151909 0.243772
min 0.000000 0.000000 0.000000
25% 0.000000 0.000000 0.625000
50% 0.000000 0.000000 0.803109
75% 0.000000 0.000000 0.937500
max 208473.000000 19159.000000 1.000000
score_rank
count 57665.000000
mean 27772.955294
std 17851.977865
min 1.000000
25% 14299.000000
50% 28832.000000
75% 43008.000000
max 55820.000000
def clean_price(price):
try:
return float(price)
except:
return None # or you can use a placeholder like 0 or -1
df['Price'] = df['Price'].apply(clean_price)
bins = [-1, 0, 10, 1000] # This means: (-1 to 0], (0 to 10], (10 to 1000]
labels = ['Free', 'Low-cost', 'Expensive']
df['Price_Category'] = pd.cut(df['Price'], bins=bins, labels=labels)
# Only quantitative columns
df_quantitative = df.select_dtypes(include=['float64', 'int64'])
# Only qualitative columns
df_qualitative = df.select_dtypes(exclude=['float64', 'int64'])
print(df.head())
AppID Name Release date Estimated owners Peak CCU \
0 20200 Galactic Bowling Oct 21, 2008 0 - 20000 0
1 655370 Train Bandit Oct 12, 2017 0 - 20000 0
2 1732930 Jolt Project Nov 17, 2021 0 - 20000 0
3 1355720 Henosis™ Jul 23, 2020 0 - 20000 0
4 1139950 Two Weeks in Painland Feb 3, 2020 0 - 20000 0
Required age Price DLC count \
0 0 19.99 0
1 0 0.99 0
2 0 4.99 0
3 0 5.99 0
4 0 0.00 0
About the game \
0 Galactic Bowling is an exaggerated and stylize...
1 THE LAW!! Looks to be a showdown atop a train....
2 Jolt Project: The army now has a new robotics ...
3 HENOSIS™ is a mysterious 2D Platform Puzzler w...
4 ABOUT THE GAME Play as a hacker who has arrang...
Supported languages ... \
0 ['English'] ...
1 ['English', 'French', 'Italian', 'German', 'Sp... ...
2 ['English', 'Portuguese - Brazil'] ...
3 ['English', 'French', 'Italian', 'German', 'Sp... ...
4 ['English', 'Spanish - Spain'] ...
Median playtime forever Median playtime two weeks Developers \
0 0 0 Perpetual FX Creative
1 0 0 Rusty Moyher
2 0 0 Campião Games
3 0 0 Odd Critter Games
4 0 0 Unusual Games
Publishers Categories \
0 Perpetual FX Creative Single-player,Multi-player,Steam Achievements,...
1 Wild Rooster Single-player,Steam Achievements,Full controll...
2 Campião Games Single-player
3 Odd Critter Games Single-player,Full controller support
4 Unusual Games Single-player,Steam Achievements
Genres \
0 Casual,Indie,Sports
1 Action,Indie
2 Action,Adventure,Indie,Strategy
3 Adventure,Casual,Indie
4 Adventure,Indie
Tags \
0 Indie,Casual,Sports,Bowling
1 Indie,Action,Pixel Graphics,2D,Retro,Arcade,Sc...
2 NaN
3 2D Platformer,Atmospheric,Surreal,Mystery,Puzz...
4 Indie,Adventure,Nudity,Violent,Sexual Content,...
Screenshots \
0 https://cdn.akamai.steamstatic.com/steam/apps/...
1 https://cdn.akamai.steamstatic.com/steam/apps/...
2 https://cdn.akamai.steamstatic.com/steam/apps/...
3 https://cdn.akamai.steamstatic.com/steam/apps/...
4 https://cdn.akamai.steamstatic.com/steam/apps/...
Movies Price_Category
0 http://cdn.akamai.steamstatic.com/steam/apps/2... Expensive
1 http://cdn.akamai.steamstatic.com/steam/apps/2... Low-cost
2 http://cdn.akamai.steamstatic.com/steam/apps/2... Low-cost
3 http://cdn.akamai.steamstatic.com/steam/apps/2... Low-cost
4 http://cdn.akamai.steamstatic.com/steam/apps/2... Free
[5 rows x 40 columns]
from sklearn.feature_extraction.text import CountVectorizer
# Remove rows with NaN 'Name' values
df = df[df['Name'].notna()]
vectorizer = CountVectorizer()
X = vectorizer.fit_transform(df['Name'])
df_vectorized = pd.DataFrame(X.toarray(), columns=vectorizer.get_feature_names_out())
print(df_vectorized.head())
00 000 001 00111 002 005 006 007 01 011 ... 피랍 학생들의 한국 현명한 \ 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 화이트래빗 회사 흡혈귀의 ３豪華限定版 ３０才の夢追い人 ４人打ちアクション麻雀 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0 0 0 0 3 0 0 0 0 0 0 4 0 0 0 0 0 0 [5 rows x 38495 columns]
#Drop non-useable columns
columns_to_drop = ['Reviews', 'Support url', 'Support email', 'Metacritic score',
'Metacritic url', 'User score', 'Score rank', 'Notes', 'Screenshots', 'Movies']
# Drop the columns
df = df.drop(columns=columns_to_drop, errors='ignore')
#Handle Missing Values
df['About the game'] = df['About the game'].fillna('No Description')
df['Supported languages'] = df['Supported languages'].fillna('No Supported Languages')
df['Full audio languages'] = df['Full audio languages'].fillna('No Audio Languages')
df['Website'] = df['Website'].fillna('No Websites')
df['Developers'] = df['Developers'].fillna('No Developers')
df['Publishers'] = df['Publishers'].fillna('No Publishers')
df['Categories'] = df['Categories'].fillna('No Categories')
df['Genres'] = df['Genres'].fillna('No Genres')
df['Tags'] = df['Tags'].fillna('No Tags')
df = df.dropna()
print(df.head())
AppID Name Release date Estimated owners Peak CCU \
0 20200 Galactic Bowling Oct 21, 2008 0 - 20000 0
1 655370 Train Bandit Oct 12, 2017 0 - 20000 0
2 1732930 Jolt Project Nov 17, 2021 0 - 20000 0
3 1355720 Henosis™ Jul 23, 2020 0 - 20000 0
4 1139950 Two Weeks in Painland Feb 3, 2020 0 - 20000 0
Required age Price DLC count \
0 0 19.99 0
1 0 0.99 0
2 0 4.99 0
3 0 5.99 0
4 0 0.00 0
About the game \
0 Galactic Bowling is an exaggerated and stylize...
1 THE LAW!! Looks to be a showdown atop a train....
2 Jolt Project: The army now has a new robotics ...
3 HENOSIS™ is a mysterious 2D Platform Puzzler w...
4 ABOUT THE GAME Play as a hacker who has arrang...
Supported languages ... \
0 ['English'] ...
1 ['English', 'French', 'Italian', 'German', 'Sp... ...
2 ['English', 'Portuguese - Brazil'] ...
3 ['English', 'French', 'Italian', 'German', 'Sp... ...
4 ['English', 'Spanish - Spain'] ...
Average playtime forever Average playtime two weeks Median playtime forever \
0 0 0 0
1 0 0 0
2 0 0 0
3 0 0 0
4 0 0 0
Median playtime two weeks Developers Publishers \
0 0 Perpetual FX Creative Perpetual FX Creative
1 0 Rusty Moyher Wild Rooster
2 0 Campião Games Campião Games
3 0 Odd Critter Games Odd Critter Games
4 0 Unusual Games Unusual Games
Categories \
0 Single-player,Multi-player,Steam Achievements,...
1 Single-player,Steam Achievements,Full controll...
2 Single-player
3 Single-player,Full controller support
4 Single-player,Steam Achievements
Genres \
0 Casual,Indie,Sports
1 Action,Indie
2 Action,Adventure,Indie,Strategy
3 Adventure,Casual,Indie
4 Adventure,Indie
Tags Price_Category
0 Indie,Casual,Sports,Bowling Expensive
1 Indie,Action,Pixel Graphics,2D,Retro,Arcade,Sc... Low-cost
2 No Tags Low-cost
3 2D Platformer,Atmospheric,Surreal,Mystery,Puzz... Low-cost
4 Indie,Adventure,Nudity,Violent,Sexual Content,... Free
[5 rows x 30 columns]
import matplotlib.pyplot as plt
import seaborn as sns
plt.figure(figsize=(15,7))
sns.countplot(data=df, y='Genres', order=df['Genres'].value_counts().index)
plt.title('Distribution of Game Genres')
plt.xlabel('Number of Games')
plt.show()
plt.figure(figsize=(15,7))
sns.countplot(data=df, x='Release date')
plt.title('Year-wise Game Releases')
plt.ylabel('Number of Games')
plt.xticks(rotation=45)
plt.show()
df['User_Score'] = df['Positive']/(df['Positive'] + df['Negative'])
top_rated = df.sort_values(by='User_Score', ascending=False).head(10) # Assuming you have a column named 'User_Score'
plt.figure(figsize=(15,7))
sns.barplot(data=top_rated, y='Name', x='User_Score', palette='viridis')
plt.title('Top 10 Rated Games')
plt.xlabel('User Score')
plt.show()
/var/folders/00/v47jm2yj45586bq73lrp36nh0000gn/T/ipykernel_55520/2896369396.py:4: FutureWarning:
Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.
sns.barplot(data=top_rated, y='Name', x='User_Score', palette='viridis')
/Users/qbs/anaconda3/lib/python3.10/site-packages/IPython/core/pylabtools.py:152: UserWarning: Glyph 36015 (\N{CJK UNIFIED IDEOGRAPH-8CAF}) missing from current font.
fig.canvas.print_figure(bytes_io, **kw)
/Users/qbs/anaconda3/lib/python3.10/site-packages/IPython/core/pylabtools.py:152: UserWarning: Glyph 27700 (\N{CJK UNIFIED IDEOGRAPH-6C34}) missing from current font.
fig.canvas.print_figure(bytes_io, **kw)
/Users/qbs/anaconda3/lib/python3.10/site-packages/IPython/core/pylabtools.py:152: UserWarning: Glyph 27133 (\N{CJK UNIFIED IDEOGRAPH-69FD}) missing from current font.
fig.canvas.print_figure(bytes_io, **kw)
plt.figure(figsize=(12,7))
sns.heatmap(df.corr(), annot=True, cmap='coolwarm')
plt.title('Correlation Heatmap')
plt.show()
/var/folders/00/v47jm2yj45586bq73lrp36nh0000gn/T/ipykernel_55520/2899654527.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning. sns.heatmap(df.corr(), annot=True, cmap='coolwarm')
plt.figure(figsize=(14, 6))
df['Categories'].value_counts().head(10).plot(kind='bar', color='lightgreen')
plt.title('Top 10 Categories by Number of Games')
plt.xlabel('Categories')
plt.ylabel('Number of Games')
plt.xticks(rotation=45)
plt.show()
plt.figure(figsize=(14, 6))
df['Publishers'].value_counts().head(10).plot(kind='bar', color='lightblue')
plt.title('Top 10 Publishers by Number of Games Released')
plt.xlabel('Publisher')
plt.ylabel('Number of Games')
plt.xticks(rotation=45)
plt.show()
df['score_rank'] = df['User_Score'].rank(ascending=False, method='min')
import matplotlib.pyplot as plt
import seaborn as sns
top_developers = df['Developers'].value_counts().index[:10]
filtered_df = df[df['Developers'].isin(top_developers)]
plt.figure(figsize=(15, 8))
sns.boxplot(x='Developers', y='score_rank', data=filtered_df)
plt.title('Distribution of Score Rank Across Top Developers')
plt.ylabel('Score Rank')
plt.xlabel('Developers')
plt.xticks(rotation=45)
plt.show()
import matplotlib.pyplot as plt
import seaborn as sns
bins = [0, 10, 20, 30, 40, 50, 60, 100, 200]
labels = ['0-10', '11-20', '21-30', '31-40', '41-50', '51-60', '61-100', '101-200']
df['price_bin'] = pd.cut(df['Price'], bins=bins, labels=labels, right=False)
plt.figure(figsize=(15, 8))
sns.boxplot(x='price_bin', y='score_rank', data=df)
plt.title('Distribution of Score Rank Across Different Price Ranges')
plt.ylabel('Score Rank')
plt.xlabel('Price Range ($)')
plt.xticks(rotation=45)
plt.show()
plt.figure(figsize=(12, 6))
sns.scatterplot(x='Price', y='score_rank', data=df, alpha=0.5)
plt.title('Scatter Plot between Score Rank and Price')
plt.ylabel('Score Rank')
plt.xlabel('Price ($)')
plt.show()
